Natural Language Processing for the Semantic Web

2016 ◽  
Vol 6 (2) ◽  
pp. 1-194 ◽  
Author(s):  
Diana Maynard ◽  
Kalina Bontcheva ◽  
Isabelle Augenstein
Keyword(s):  
Natural Language Processing ◽  
Semantic Web ◽  
Natural Language ◽  
Language Processing

scholarly journals Ontology evolution: a process-centric survey

2013 ◽  
Vol 30 (1) ◽  
pp. 45-75 ◽  
Author(s):  
Fouad Zablith ◽  
Grigoris Antoniou ◽  
Mathieu d'Aquin ◽  
Giorgos Flouris ◽  
Haridimos Kondylakis ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Information Systems ◽  
Semantic Web ◽  
Natural Language ◽  
Language Processing ◽  
Process Model ◽  
Ontology Evolution ◽  
Depth Analysis ◽  
Future Challenges ◽  
Industrial Adoption

AbstractOntology evolution aims at maintaining an ontology up to date with respect to changes in the domain that it models or novel requirements of information systems that it enables. The recent industrial adoption of Semantic Web techniques, which rely on ontologies, has led to the increased importance of the ontology evolution research. Typical approaches to ontology evolution are designed as multiple-stage processes combining techniques from a variety of fields (e.g., natural language processing and reasoning). However, the few existing surveys on this topic lack an in-depth analysis of the various stages of the ontology evolution process. This survey extends the literature by adopting a process-centric view of ontology evolution. Accordingly, we first provide an overall process model synthesized from an overview of the existing models in the literature. Then we survey the major approaches to each of the steps in this process and conclude on future challenges for techniques aiming to solve that particular stage.

Natural Language Processing as a Foundation of the Semantic Web

2007 ◽  
Vol 1 (3–4) ◽  
pp. 199-327 ◽  
Author(s):  
Yorick Wilks ◽  
Christopher Brewster
Keyword(s):  
Natural Language Processing ◽  
Semantic Web ◽  
Natural Language ◽  
Language Processing

Natural Language Processing Agents and Document Clustering in Knowledge Management

2011 ◽  
pp. 476-498 ◽  
Author(s):  
Steve Legrand ◽  
JRG Pulido
Keyword(s):  
Knowledge Management ◽  
Natural Language Processing ◽  
Semantic Web ◽  
Natural Language ◽  
Language Processing ◽  
Information Presentation ◽  
Processing Methods ◽  
Standard Format ◽  
Web Technologies ◽  
The Web

While HTML provides the Web with a standard format for information presentation, XML has been made a standard for information structuring on the Web. The mission of the Semantic Web now is to provide meaning to the Web. Apart from building on the existing Web technologies, we need other tools from other areas of science to do that. This chapter shows how natural language processing methods and technologies, together with ontologies and a neural algorithm, can be used to help in the task of adding meaning to the Web, thus making the Web a better platform for knowledge management in general.

Iq Semantic: Semantic Web Intelligent Querying Framework

2020 ◽  
Vol 26 (3) ◽  
pp. 103-107
Author(s):  
Ilie Cristian Dorobăţ ◽  
Vlad Posea
Keyword(s):  
Natural Language Processing ◽  
Semantic Web ◽  
Natural Language ◽  
Language Processing ◽  
Open Data ◽  
Linked Open Data ◽  
Semantic Data ◽  
The Web

AbstractThe continuous expansion of the semantic web and of the linked open data cloud meant more semantic data are available for querying from endpoints all over the web. We propose extending a standard SPARQL interface with UI and Natural Language Processing features to allow easier and more intelligent querying. The paper describes some usage scenarios for easy querying and launches a discussion on the advantages of such an implementation.

NLP and the Representation of Data on the Semantic Web

2021 ◽  
pp. 393-426
Author(s):  
Jose L. Martinez-Rodriguez ◽  
Ivan Lopez-Arevalo ◽  
Jaime I. Lopez-Veyna ◽  
Ana B. Rios-Alvarado ◽  
Edwin Aldana-Bobadilla
Keyword(s):  
Natural Language Processing ◽  
Semantic Web ◽  
Natural Language ◽  
Language Processing ◽  
Resource Description Framework ◽  
Basic Unit ◽  
Starting Point ◽  
Description Framework ◽  
Resource Description

One of the goals of data scientists and curators is to get information (contained in text) organized and integrated in a way that can be easily consumed by people and machines. A starting point for such a goal is to get a model to represent the information. This model should ease to obtain knowledge semantically (e.g., using reasoners and inferencing rules). In this sense, the Semantic Web is focused on representing the information through the Resource Description Framework (RDF) model, in which the triple (subject, predicate, object) is the basic unit of information. In this context, the natural language processing (NLP) field has been a cornerstone in the identification of elements that can be represented by triples of the Semantic Web. However, existing approaches for the representation of RDF triples from texts use diverse techniques and tasks for such purpose, which complicate the understanding of the process by non-expert users. This chapter aims to discuss the main concepts involved in the representation of the information through the Semantic Web and the NLP fields.

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